The present disclosure relates generally to selecting useful predictors for linear modeling and, more specifically, to selecting useful channels for non-invasive medical devices.
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
In the field of medicine, doctors often desire to monitor certain physiological characteristics of their patients. Accordingly, a wide variety of devices may have been developed for monitoring many such characteristics of a patient. Such devices may provide doctors and other healthcare personnel with the information they need to provide the best possible healthcare for their patients. As a result, such monitoring devices have become useful in treating patients.
Non-invasive medical devices may be particularly useful and desirable, as they generally provide immediate feedback and do not traumatize a patient. Generally, non-invasive sensors may transmit electromagnetic radiation, such as light, through a patient's tissue. The sensor may photoelectrically detect the absorption and scattering of the transmitted light in such tissue. The light passed through the tissue may be selected to be of one or more wavelengths that may be absorbed and scattered by particular tissue constituents, such as blood, for example. One or more physiological characteristics may then be calculated based upon the amount of light absorbed and/or scattered.
One non-invasive technique for monitoring certain physiological characteristics of a patient is commonly referred to as pulse oximetry, and the devices built based upon pulse oximetry techniques are commonly referred to as pulse oximeters. Pulse oximetry may be used to measure various blood flow characteristics, such as the blood-oxygen saturation of hemoglobin in arterial blood, the volume of individual blood pulsations supplying the tissue, and/or the rate of blood pulsations corresponding to each heartbeat of a patient. In fact, the “pulse” in pulse oximetry refers to the time varying amount of arterial blood in the tissue during each cardiac cycle. Pulse oximetry readings may measure the pulsatile, dynamic changes in amount and type of blood constituents in tissue.
However, in pulse oximetry, as well as other non-invasive monitoring techniques, the investigative instruments (e.g., NIR spectroscopes) commonly allow measurements in more discrete channels than the relevant underlying degrees of freedom or the number of objects under investigation. While a wide array of channels may provide greater predictive power, some channels may confound prediction of the relevant response, essentially measuring only “noise.” Moreover, the principle of parsimony dictates that a predictive model must focus on as few of the channels as practical, or fewer.